Second Order Analysis for Joint Source-Channel Coding With General Channel and Markovian Source - Yaguchi, Ryo; Hayashi, Masahito (IEEE transactions on information theory, 2019)
We derive the optimal second-order rates in joint source-channel coding when the channel is a general discrete memoryless channel and the source is an irreducible and ergodic Markov process. In contrast, previous studies solved it only when the channel satisfies a certain unique-variance condition and the source is subject to an independent and identical distribution. We also compare the joint source-channel scheme with the separation scheme in the second-order regime, while a previous study made a notable comparison with numerical calculation. To discuss these two topics, we introduce two kinds of new distribution families, switched Gaussian convolution distribution and *-product distribution, which are defined by modifying the Gaussian distribution.